Collateral fitness effects of mutations

Abstract

<jats:p>The distribution of fitness effects of mutation plays a central role in constraining protein evolution. The underlying mechanisms by which mutations lead to fitness effects are typically attributed to changes in protein specific activity or abundance. Here, we reveal the importance of a mutation’s collateral fitness effects, which we define as effects that do not derive from changes in the protein’s ability to perform its physiological function. We comprehensively measured the collateral fitness effects of missense mutations in the<jats:italic>Escherichia coli TEM-1</jats:italic>β-lactamase antibiotic resistance gene using growth competition experiments in the absence of antibiotic. At least 42% of missense mutations in<jats:italic>TEM-1</jats:italic>were deleterious, indicating that for some proteins collateral fitness effects occur as frequently as effects on protein activity and abundance. Deleterious mutations caused improper posttranslational processing, incorrect disulfide-bond formation, protein aggregation, changes in gene expression, and pleiotropic effects on cell phenotype. Deleterious collateral fitness effects occurred more frequently in<jats:italic>TEM-1</jats:italic>than deleterious effects on antibiotic resistance in environments with low concentrations of the antibiotic. The surprising prevalence of deleterious collateral fitness effects suggests they may play a role in constraining protein evolution, particularly for highly expressed proteins, for proteins under intermittent selection for their physiological function, and for proteins whose contribution to fitness is buffered against deleterious effects on protein activity and protein abundance.</jats:p>

The Relationship between the Misfolding Avoidance Hypothesis and Protein Evolutionary Rates in the Light of Empirical Evidence

“…2019 ). Recently, the fraction of mutations leading to deleterious effects through all possible nonfunctional mechanisms, referred to as collateral effects, was estimated to be approximately 40% for the TEM-1 protein in E. coli ( Mehlhoff et al. 2020 ).…”

“…And this assumption is quite unlikely as protein sites of collateral mutations substantially overlap with functionally sensitive sites, and collateral effects are often smaller in magnitude compared with functional effects ( Stiffler et al. 2015 ; Mehlhoff et al. 2020 ).…”

Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation

“…In order to test this model and better understand the genotype-phenotype-fitness map, we face the difficult task of identifying which phenotypes are affected by the adaptive mutations and then determining how these phenotypes contribute to fitness. This is a challenging problem as the possible number of phenotypes one can measure is effectively infinite, for example the expression level of every gene or the quantity of every metabolite ( Coombes et al, 2019 ; Mehlhoff et al, 2020 ). Further, many measurable phenotypes are related in complex ways ( Geiler-Samerotte et al, 2020 ).…”

Environmental selection and epistasis in an empirical phenotype-environment-fitness landscape

“…Our empirical model can also provide a quantitative understanding of the mechanisms underlying mutational epistasis, i.e., the non-additive interaction between mutational effects (Domingo et al, 2019;Starr and Thornton, 2016). Epistasis is a key phenomenon in protein evolution that dictates the shape and ruggedness of fitness landscapes, which subsequently affect important evolutionary phenomenon such as robustness (Bershtein et al, 2013(Bershtein et al, , 2006Hartl et al, 1985;Lundin et al, 2018;Tokuriki and Tawfik, 2009), evolvability (Dean, 1995;DePristo et al, 2005;Lunzer et al, 2005;Mehlhoff et al, 2020;Sarkisyan et al, 2016;Stiffler et al, 2015;Tokuriki and Tawfik, 2009;Yang et al, 2019) and evolutionary contingency (Baier et al, 2019;Starr et al, 2017;Starr and Thornton, 2016). One form of epistasis, defined as 'nonspecific epistasis', is known to be highly prevalent and strongly influences the accessibility of mutations.…”

“…In this model, the fitness conferred by variants with biochemical traits above a certain selection 'threshold' would saturate or plateau, while fitness rapidly decreases for variants below the threshold of the trait. Such models have been widely recognized conceptually, and provide molecular explanations for important evolutionary phenomenon such as nonspecific epistasis (Bershtein et al, 2006;Dasmeh and Serohijos, 2018;Diss and Lehner, 2018;Kemble et al, 2019;Pokusaeva et al, 2019), mutational robustness (Bershtein et al, 2013(Bershtein et al, , 2006Hartl et al, 1985;Lundin et al, 2018;Tokuriki and Tawfik, 2009) and evolvability (Dean, 1995;DePristo et al, 2005;Lunzer et al, 2005;Mehlhoff et al, 2020;Sarkisyan et al, 2016;Stiffler et al, 2015;Tokuriki and Tawfik, 2009). However, quantitative and experimental studies of the threshold model are rare, as most reports contain just a handful of data points and each landscape is confined to the scope of a single level of selection pressure (Bershtein et al, 2013;Dean, 1995;Hartl et al, 1985;Lunzer et al, 2005;Pokusaeva et al, 2019).…”